Content-Based Systems are recommendation systems that suggest items based on the characteristics of the content itself. They analyze the features of items, such as keywords, genres, or descriptions, to find similarities with user preferences. For example, if a user enjoys science fiction books, the system may recommend other books with similar themes or styles. These systems rely heavily on the content's attributes rather than user behavior or ratings. They are commonly used in platforms like Netflix or Spotify, where users receive personalized suggestions based on their past interactions and the specific qualities of the media they consume.