LabelEncoder raises errors with string and string[pyarrow] types

**Describe the issue**:

Using the label encode with `string` and `string[pyarrow]` dtypes raises TypeErrors. The error is getting raised in dask.

```
File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask/array/utils.py", line 57, in meta_from_array
x = x(shape=(0,) * (ndim or 0), dtype=dtype)
TypeError: Cannot interpret 'string[pyarrow]' as a data type
```

...But I can't trigger this without the LabelEncoder.

**Minimal Complete Verifiable Example**:

```python
import dask.dataframe as dd
from dask_ml.preprocessing import LabelEncoder
import pandas as pd

df = pd.DataFrame({
"A": list("aaaabbbcccdddeeefffgggg")
})

ddf = dd.from_pandas(df, npartitions=3)

# works
lenc = LabelEncoder().fit(ddf["A"])

# TypeError: Cannot interpret 'string[pyarrow]' as a data type
lenc = LabelEncoder().fit(ddf["A"].astype("string[pyarrow]"))
```

**Full Traceback**:

Very similar tracebacks for `string` and `string[pyarrow]`

➜ python label_encoder_repro.py

Traceback (most recent call last):

  File "/Users/paul/work/sources/dask-engineering/example-pipelines/criteo-HPO/label_encoder_repro.py", line 12, in 

    lenc = LabelEncoder().fit(ddf["A"].astype("string[pyarrow]"))

  File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask_ml/preprocessing/label.py", line 115, in fit

    y = self._check_array(y)

  File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask_ml/preprocessing/label.py", line 111, in _check_array

    y = y.to_dask_array(lengths=True)

  File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask/dataframe/core.py", line 1687, in to_dask_array

    arr = self.values

  File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask/dataframe/core.py", line 3431, in values

    return self.map_partitions(methods.values)

  File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask/dataframe/core.py", line 874, in map_partitions

    return map_partitions(func, self, *args, **kwargs)

  File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask/dataframe/core.py", line 6701, in map_partitions

    return new_dd_object(graph, name, meta, divisions)

  File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask/dataframe/core.py", line 7835, in new_dd_object

    return da.Array(dsk, name=name, chunks=chunks, dtype=meta.dtype)

  File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask/array/core.py", line 1335, in __new__

    meta = meta_from_array(meta, dtype=dtype)

  File "/Users/paul/mambaforge/envs/ml-example/lib/python3.10/site-packages/dask/array/utils.py", line 57, in meta_from_array

    x = x(shape=(0,) * (ndim or 0), dtype=dtype)

TypeError: Cannot interpret 'string[pyarrow]' as a data type

**Environment**:

- Dask version: 2012.12.0
- Python version: 3.10
- Operating System: M1 Mac
- Install method (conda, pip, source): conda

Start by running the self-contained example with the reported Dask and pandas string dtypes, then inspect dask_ml/preprocessing/label.py, especially LabelEncoder.fit and _check_array. Trace the conversion into Dask arrays shown in the traceback, and verify that fitting both string and string[pyarrow] inputs completes without a TypeError.

Written by the indexing model from the issue text.