Hierarchical clustering is an unsupervised machine learning technique used to group similar data points into a tree-like structure known as a dendrogram. It creates a hierarchy of clusters by either agglomerative (bottom-up) or divisive (top-down) approaches. This method is particularly useful for exploratory data analysis and visualization of data relationships.