Explanation:

The correct answer is option 'B' - Pickle.

Serialization and De-serialization:
Serialization is the process of converting a Python object into a byte stream, which can be stored in a file or transmitted over a network. De-serialization is the reverse process of converting the byte stream back into a Python object.

Pickle Module:
The pickle module in Python is used for serialization and de-serialization of Python object structures. It provides functions for serializing objects into a byte stream and de-serializing them back into Python objects. The pickle module can handle almost all Python objects, including complex data structures like lists, dictionaries, and user-defined objects.

Serializing with Pickle:
To serialize an object using pickle, the dump() function is used. This function takes two arguments - the object to be serialized and the file object to which the serialized data will be written. The dump() function writes the serialized object as a byte stream to the specified file.

Deserializing with Pickle:
To de-serialize an object using pickle, the load() function is used. This function takes a single argument - the file object from which the serialized data will be read. The load() function reads the byte stream from the file and converts it back into a Python object.

Example:

Here is an example that demonstrates the use of the pickle module for serialization and de-serialization:

```python
import pickle

# Serialize an object
data = {'name': 'John', 'age': 30}
with open('data.pickle', 'wb') as file:
pickle.dump(data, file)

# Deserialize an object
with open('data.pickle', 'rb') as file:
data = pickle.load(file)
print(data)
```

In this example, the dictionary `data` is serialized using the dump() function and saved to a file called 'data.pickle'. Then, the same file is opened and the serialized data is de-serialized using the load() function. The de-serialized object is printed, which outputs the original dictionary `data`.

Conclusion:

The pickle module in Python is used for serializing and de-serializing any Python object structure. It provides functions like dump() and load() to perform the serialization and de-serialization processes.