Hierarchical clustering is a method used to group similar items together based on their characteristics. There are two main approaches: agglomerative (bottom-up) and divisive (top-down). Different ways of measuring the distance between clusters lead to various clustering techniques. Divisive algorithms like DIANA split clusters into smaller ones until each cluster contains only one item. MONA focuses on binary variables.