FeatureUnion with polars output fails due to missing column renaming in adapter interface

### Describe the bug

When using `FeatureUnion` with `set_config(transform_output="polars")`, the operation fails with `polars.exceptions.DuplicateError` because the `ContainerAdapterProtocol.hstack()` interface is incomplete - it doesn't accept `feature_names` parameter to apply column renaming before concatenation.

The `verbose_feature_names_out=True` (default) mechanism should ensure unique column names via `get_feature_names_out()`, but this information cannot be passed to the adapter's `hstack()` method due to interface design limitation.

### Steps/Code to Reproduce

```python
from sklearn.pipeline import FeatureUnion
from sklearn.preprocessing import StandardScaler
from sklearn import set_config
import numpy as np
set_config(transform_output="polars")
X = np.array([[1, 2], [3, 4], [5, 6]])
union = FeatureUnion([
    ("scaler1", StandardScaler()),
    ("scaler2", StandardScaler())
])
result = union.fit_transform(X)
```

### Expected Results

The code should work and produce a polars DataFrame with uniquely named columns like `['scaler1__x0', 'scaler1__x1', 'scaler2__x0', 'scaler2__x1']`, consistent with the design of `verbose_feature_names_out=True`.

### Actual Results

```python
Traceback (most recent call last):
  File "<stdin>", line 10, in <module>
  File "/path/to/sklearn/utils/_set_output.py", line 316, in wrapped
    data_to_wrap = f(self, X, *args, **kwargs)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/path/to/sklearn/pipeline.py", line 1971, in fit_transform
    return self._hstack(Xs)
           ^^^^^^^^^^^^^^^^
  File "/path/to/sklearn/pipeline.py", line 2052, in _hstack
    return adapter.hstack(Xs)
           ^^^^^^^^^^^^^^^^^^
  File "/path/to/sklearn/utils/_set_output.py", line 183, in hstack
    return pl.concat(Xs, how="horizontal")
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/path/to/polars/functions/eager.py", line 256, in concat
    out = wrap_df(plr.concat_df_horizontal(elems))
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
polars.exceptions.DuplicateError: column with name 'x0' has more than one occurrence
```

### Versions

```shell
System:
    python: 3.11.14 | packaged by conda-forge | (main, Oct 22 2025, 22:46:25) [GCC 14.3.0]
executable: /opt/conda/envs/sklearn-dev/bin/python
   machine: Linux-6.8.0-65-generic-x86_64-with-glibc2.36

Python dependencies:
      sklearn: 1.9.dev0
          pip: 25.3
   setuptools: 80.9.0
        numpy: 2.3.5
        scipy: 1.16.3
       Cython: 3.2.2
       pandas: 2.3.3
   matplotlib: None
       joblib: 1.5.2
threadpoolctl: 3.6.0

Built with OpenMP: True

threadpoolctl info:
       user_api: blas
   internal_api: openblas
    num_threads: 48
         prefix: libopenblas
       filepath: /opt/conda/envs/sklearn-dev/lib/libopenblasp-r0.3.30.so
        version: 0.3.30
threading_layer: pthreads
   architecture: SkylakeX

       user_api: openmp
   internal_api: openmp
    num_threads: 48
         prefix: libgomp
       filepath: /opt/conda/envs/sklearn-dev/lib/libgomp.so.1.0.0
        version: None
```

COMMENT:
Thanks for the high quality report. I confirm I can reproduce the problem.

Labels: Bug