DataFrame to Arrow Table Conversion issue with Tuple datatype

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

While attempting to convert a DataFrame containing a column with tuples to an Arrow Table and back to a DataFrame, we encountered a discrepancy (expected tuple, got np.ndarray) between the original DataFrame and the DataFrame obtained from the Arrow Table.

Steps to Reproduce:

1. Create a DataFrame with a column that contains tuples.
2. Convert the DataFrame to an Arrow Table using pa.Table.from_pandas().
3. Convert the Arrow Table back to a DataFrame using table.to_pandas().
4. Compare the original DataFrame with the DataFrame obtained from the Arrow Table.

Expected Results:

The DataFrames before and after conversion should be identical.

Actual Results:

The DataFrames differ.

```

import pandas as pd
import pyarrow as pa

data = {'tup': [(1, 2), (3, 4), (5, 6)]}
df = pd.DataFrame(data)

table = pa.Table.from_pandas(df)
df_back = table.to_pandas()

print("Original DataFrame:")
print(df)

print("\nDataFrame converted from Arrow Table:")
print(df_back)

print("\nAre the DataFrames equal?", df.equals(df_back))

```


### Component(s)

Python

Start with the reproducer in the issue using pandas and pyarrow, then inspect the Python component responsible for pa.Table.from_pandas() and table.to_pandas(). Verify the tuple column's values before and after the round trip; done means the resulting DataFrame matches the original and df.equals(df_back) succeeds.

Written by the indexing model from the issue text.