Text clustering is a process of grouping similar pieces of text together based on different characteristics. It is a form of unsupervised learning where the clusters are formed without any prior information or labels given to the data. In the clustering process, the text is analyzed and grouped according to its semantic meaning and content. Text clustering can be used to identify the main topics of a large collection of documents, as well as to discover relationships between documents.