Distributed data mining deals with the problem of data analysis in environments with distributed data, computing nodes, and users. Peer-to-peer computing is emerging as a new distributed computing paradigm for many novel applications that involve exchange of information among a large number of peers with little centralized coordination. Peerto-peer file sharing, peer-to-peer electronic commerce, and peer-to-peer monitoring based on a network of sensors are some examples. This paper offers an overview of distributed data mining applications and algorithms for peer-to-peer environments. It describes both exact and approximate distributed data mining algorithms that work in a decentralized manner. It illustrates these approaches for the problem of computing and monitoring clusters in the data residing at the different nodes of a peer-to-peer network.