The silhouette score is a metric used to evaluate the quality of clusters in a clustering algorithm by measuring how similar an object is to its own cluster compared to other clusters. A higher silhouette score indicates that the object is well-matched to its own cluster and poorly matched to neighboring clusters, thus reflecting more distinct and well-separated clusters.