Clustering and classification are different machine learning techniques with distinct goals.

Classification is about sorting into known categories (like sorting mail into pre-labeled boxes). Clustering, on the other hand, is about discovering categories (like finding groups in unsorted mail).

Classification is commonly used in spam detection or image recognition, where the categories are predefined. On the other hand, clustering is used in scenarios like customer segmentation or discovering topics in a collection of documents, where the goal is to reveal hidden patterns or groupings.

In short, classification is about predicting known categories, while clustering helps discover unknown groupings. The choice between the two depends on the nature of your data and the problem you're trying to solve.