In Artificial Intelligence, Clustering is a type of unsupervised learning that is training a model on the unlabeled data. In simple words, clustering is a grouping of similar observations in one cluster and dissimilar observations in another cluster. The similarity between the observations is calculated by using similarity measures such as Euclidean distance, Manhattan distance, Cosine similarity, Jaccard distance, or Minkowski distance. There are three types of clustering algorithms such as Partitional clustering, density-based clustering, Hierarchal clustering. The most used clustering algorithms are K-means, DBSCAN, Agglomerative clustering.
If you want to learn and implement clustering algorithms, I would recommend this Machine Learning course by Intellipaat