This package provides several clustering algorithm implementations. Clustering usually groups a set of objects into groups of similar items. The definition of similarity usually is up to you - for text documents, cosine-distance/-similarity is recommended. Mahout also features other types of distance measure like Euclidean distance.
Input of each clustering algorithm is a set of vectors representing your items. For texts in general these are TFIDF or Bag of words representations of the documents.
Output of each clustering algorithm is either a hard or soft assignment of items to clusters.