Which of the following best describes a classification algorithm?

A classification algorithm is designed to predict a category or class label for a given data point based on its features. This process involves learning from a labeled dataset, where the algorithm identifies underlying patterns to assign new, unseen data points to the correct category. For instance, in a spam detection system, a classification algorithm would learn from previously labeled emails to categorize new emails as either "spam" or "not spam."

The focus of classification algorithms is on discrete outcomes, contrasting with regression algorithms that predict continuous values. While some options mention algorithms that handle grouping or storage of data, these describe different functions. Grouping items together pertains to clustering algorithms, which do not require labeled data for categorization, and storing data refers more to database management rather than classification tasks. Hence, the description of predicting a category for a data point accurately captures the core purpose and function of classification algorithms.