Support custom feature types
### Feature request

I think it would be nice to allow registering custom feature types with the 🤗 Datasets library. For example, allow to do something along the following lines:

```
from datasets.features import register_feature_type  # this would be a new function

@register_feature_type
class CustomFeatureType:
    def encode_example(self, value):
        """User-provided logic to encode an example of this feature."""
        pass

    def decode_example(self, value, token_per_repo_id=None):
        """User-provided logic to decode an example of this feature."""
        pass
```

### Motivation

Users of 🤗 Datasets, such as myself, may want to use the library to load datasets with unsupported feature types (i.e., beyond `ClassLabel`, `Image`, or `Audio`). This would be useful for prototyping new feature types and for feature types that aren't used widely enough to warrant inclusion in 🤗 Datasets.

At the moment, this is only possible by monkey-patching 🤗 Datasets, which obfuscates the code and is prone to breaking with library updates. It also requires the user to write some custom code which could be easily avoided.

### Your contribution

I would be happy to contribute this feature. My proposed solution would involve changing the following call to `globals()` to an explicit feature type registry, which a user-facing `register_feature_type` decorator could update.

https://github.com/huggingface/datasets/blob/fd893098627230cc734f6009ad04cf885c979ac4/src/datasets/features/features.py#L1329

I would also provide an abstract base class for custom feature types which users could inherit. This would have at least an `encode_example` method and a `decode_example` method, similar to `Image` or `Audio`.

The existing `encode_nested_example` and `decode_nested_example` functions would also need to be updated to correctly call the corresponding functions for the new type.