Explain the working of the content-based filtering recommendation algorithm?

It is a type of Machine Learning technique in which decisions can be made using similar features.

This method compares the user interests to product features.

In this algorithm, users define an item using a keyword or an attribute, and a user profile is created with the help of these attributes. After that, items are ranked based on how closely they match the user attribute profile, and then the best match is recommended.