[Python] pa.Table.to_pandas(zero_copy_only=True) never succeeds

### Describe the bug, including details regarding any error messages, version, and platform.

When converting a Table to pandas, adding the `zero_copy_only=True` argument makes it always fail with ArrowInvalid.

```python
In [17]: table = pa.table({'a': [1.0, 2.0, 3.0], 'b': ['x','y','z']})

In [19]: table.schema
Out[19]:
a: double
b: string

In [20]: table.to_pandas(zero_copy_only=True)
...
ArrowInvalid: Cannot do zero copy conversion into multi-column DataFrame block
```
Note that this is a similar bug report to #38644, but in that case the interaction with `types_mapper` is considered to be the reason for the Exception, whereas I found it is happening even without setting type mapping.

The keyword works fine for ChunkedArray conversions:
```python
In [23]: table['a'].to_pandas(zero_copy_only=True)
Out[23]:
0 1.0
1 2.0
2 3.0
Name: a, dtype: float64
```
even when adding type mapping to pandas Arrow types:
```python
In [22]: table['a'].to_pandas(zero_copy_only=True, types_mapper=pd.ArrowDtype)
Out[22]:
0 1.0
1 2.0
2 3.0
Name: a, dtype: double[pyarrow]
```
and fails on non-zero copy operations, like string to categorical conversion:
```python
In [28]: table['b'].to_pandas(zero_copy_only=True, strings_to_categorical=True)
ArrowInvalid: Need to dictionary encode a column, but only zero-copy conversions allowed
```

Is this expected behaviour? I.e., should the argument always flag `Table -> DataFrame` conversions as not being zero copy? In that case, it might make sense to remove the argument from `pa.Table.to_pandas` altogether, as it will always result in an exception thrown.

### Component(s)

Python