Hierarchical clustering initially creates as many clusters as there are instances in the dataset. Each cluster contains only a single instance. Following this, it repeatedly finds the two clusters with the minimum distance between them (for example, the Euclidean distance), and merges them together into a new cluster. The process ends when there is only a single cluster. The method's output is a dendrogram, which indicates how instances are hierarchically organized. An example is depicted in the following figure: