BUG: Sliced subclassed Series returns full data result when custom method is applied
- [x] I have checked that this issue has not already been reported.

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

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

---


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

```python
import pandas as pd

class _Subseries(pd.Series):

   _metadata = ['custom_method']

   @property
   def _constructor(self):
       return _Subseries

   @property
   def _constructor_expanddim(self):
       return _Subseries

   def custom_method(self, value):
       return self + value

s = _Subseries(range(5))
s = s.iloc[-3:]
s.custom_method(1)
```

#### Problem description

The above code returns:
0&nbsp;&nbsp;&nbsp;1
1&nbsp;&nbsp;&nbsp;2
2&nbsp;&nbsp;&nbsp;3
3&nbsp;&nbsp;&nbsp;4
4&nbsp;&nbsp;&nbsp;5

A similar method, such as .add(), on a sliced Series will return the result of that method on the sliced data and not on the original full data. I would expect this to be the same in a subclassed version of a Series.

#### Expected Output
2&nbsp;&nbsp;&nbsp;3
3&nbsp;&nbsp;&nbsp;4
4&nbsp;&nbsp;&nbsp;5


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

<details>

INSTALLED VERSIONS
------------------
commit           : 67a3d4241ab84419856b84fc3ebc9abcbe66c6b3
python           : 3.9.0.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18362
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_Belgium.1252

pandas           : 1.1.4
numpy            : 1.19.4
pytz             : 2020.4
dateutil         : 2.8.1
pip              : 20.3.1
setuptools       : 49.6.0.post20201009
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
