BUG: Pandas DataFrame replace() doesn't work if the dataframe has nullable boolean columns
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [X] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
import pandas as pd
df = pd.DataFrame({"a": ["x", "y", "z", "w"], "b": [True, False, False, True]}).astype({"b":"boolean"})
df.replace("x", "X")
```


### Issue Description

When trying to use `pandas.DataFrame.replace()` on a dataframe with several columns including boolean columns where the `boolean` (i.e. nullable) dtype has been set explicitly beforehand. When running the above snippet I get the following error:

```
File "C:\users\el_caminooooo\playground\venv/lib/python3.7/site-packages/pandas/core/arrays/boolean.py", line 265, in __init__
    "values should be boolean numpy array. Use "
TypeError: values should be boolean numpy array. Use the 'pd.array' function instead
```

Is this a pandas bug?. Also please note both of the following work fine:

```python
import pandas as pd
df = pd.DataFrame({"a": ["x", "y", "z", "w"], "b": [True, False, False, True]}).astype({"b":"bool"})  # notice 'bool' instead of 'boolean'
df.replace("x", "X")
```

and:

```python
df = pd.DataFrame({"a": ["x", "y", "z", "w"], "b": [True, False, False, True]})
df.replace("x", "X")
```

### Expected Behavior

the replace should complete successfully

### Installed Versions

<details>
INSTALLED VERSIONS
------------------
commit           : 7c48ff4409c622c582c56a5702373f726de08e96
python           : 3.7.10.final.0
python-bits      : 64
OS               : Linux
OS-release       : 3.10.0-957.27.2.el7.x86_64
Version          : #1 SMP Mon Jul 29 17:46:05 UTC 2019
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8
pandas           : 1.3.4
numpy            : 1.21.0
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.3.1
setuptools       : 47.1.0
Cython           : 0.29.23
pytest           : 6.2.5
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.0.1
IPython          : None
pandas_datareader: 0.10.0
bs4              : None
bottleneck       : None
fsspec           : 2021.08.1
fastparquet      : 0.7.0
gcsfs            : None
matplotlib       : 3.4.2
numexpr          : None
odfpy            : None
openpyxl         : 3.0.9
pandas_gbq       : None
pyarrow          : 4.0.0
pyxlsb           : None
s3fs             : None
scipy            : 1.6.3
sqlalchemy       : None
tables           : None
tabulate         : 0.8.9
xarray           : None
xlrd             : None
xlwt             : None
numba            : None</details>
