A company wants to group its customer base to understand different customer groups.

Clustering is an unsupervised machine learning technique used to group data points based on similarity without requiring labeled data. AWS documentation explains that clustering is commonly used for customer segmentation, where the goal is to discover natural groupings within a dataset.

In this scenario, the dataset is unlabeled and includes behavioral and demographic features. Clustering algorithms analyze patterns and distances between data points to identify distinct customer groups, making this technique ideal for understanding customer segments.

Regression and classification require labeled outputs, and reinforcement learning focuses on sequential decision-making, not grouping. AWS positions clustering as the correct approach for this use case.