Content-Based Filtering is a recommendation system technique that suggests items based on the features of the items themselves. For example, if you enjoy movies like Inception and The Matrix, the system analyzes their characteristics, such as genre, director, and actors, to recommend similar films. This approach focuses on the content of the items rather than user behavior. This method is particularly useful for personalized recommendations, as it tailors suggestions to individual preferences. By understanding what you like, the system can recommend new items that match your tastes, such as books, music, or articles, enhancing your overall experience with streaming services or e-commerce platforms.