Python’s memory allocation and deallocation method is automatic. The user does not have to preallocate or deallocate memory similar to using dynamic memory allocation in languages such as C or C++. 
Python uses two strategies for memory allocation: 

Reference counting

Garbage collection

Prior to Python version 2.0, the Python interpreter only used reference counting for memory management. Reference counting works by counting the number of times an object is referenced by other objects in the system. When references to an object are removed, the reference count for an object is decremented. When the reference count becomes zero, the object is deallocated. Ex- 

Garbage collection is the process of automatically reclaiming memory that is no longer being used by a program. In Python, this is handled by the built-in garbage collector.

Python's garbage collector runs periodically to identify and remove objects that are no longer in use by the program. It does this by keeping track of which objects are being referenced by the program and which are not. Objects that are no longer referenced are marked for deletion, and the memory they occupy is released.

One of the benefits of garbage collection is that it allows programmers to focus on writing code rather than worrying about memory management. Since Python handles memory management automatically, developers can spend more time on other aspects of the program.

However, garbage collection does come with some overhead, as the collector must run periodically to check for objects that are no longer being used. This can lead to some performance overhead in programs that use a lot of memory or have a high volume of objects being created and destroyed.

Overall, garbage collection is a useful feature in Python that simplifies memory management and makes programming easier for developers.