BUG: pd.DataFrame.replace(to_replace: list, method: str) raises TypeError: No matching signature found
- [x] I have checked that this issue has not already been reported: [search query](https://github.com/pandas-dev/pandas/issues?page=2&q=is%3Aissue+is%3Aopen+replace+Categorical)

- [ ] I have confirmed this bug exists on the latest version of pandas.

- [x] (optional) I have confirmed this bug exists on the master branch of pandas: Tested with '1.2.0.dev0+1137.g50b34a4a8')

---

#### Code Sample, a copy-pastable example

```python
import pandas as pd

df = pd.DataFrame({
    'x': pd.Categorical([1, 2, 3], [1, 2, 3])
})

df.replace([1, 2], method='bfill')

# > Traceback excerpt: 635 def backfill_inplace(algos_t[:] values, const uint8_t[:] mask, limit=None):
# > TypeError: No matching signature found
```

#### Problem description

This should work fine, within bounds of considerations like #18250.

#### Expected Output

Should be equivalent to `pd.Categorical([3, 3, 3], [1,2,3])` (or `pd.Categorical([3, 3, 3], [3])` depending on the what's done with unused categories elsewhere.)

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : 50b34a4a8008b6da24c3dac6ae6d66536e463239
python           : 3.8.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.4.0
Version          : Darwin Kernel Version 19.4.0: Wed Mar  4 22:28:40 PST 2020; root:xnu-6153.101.6~15/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_GB.UTF-8
LOCALE           : en_GB.UTF-8

pandas           : 1.2.0.dev0+1137.g50b34a4a8
numpy            : 1.18.5
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 47.3.1.post20200616
Cython           : 0.29.21
pytest           : 5.4.3
hypothesis       : 5.16.2
sphinx           : 3.1.1
blosc            : None
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : 4.5.1
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.15.0
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.3.2
fsspec           : 0.7.4
fastparquet      : 0.4.0
gcsfs            : None
matplotlib       : 3.2.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : 0.17.1
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.4.1
sqlalchemy       : 1.3.17
tables           : 3.6.1
tabulate         : 0.8.7
xarray           : 0.15.1
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.48.0

</details>

Noticed while working on #32542