Email spam is considered as a probable intimidation to an email user. Sometimes spam can even lead to unnecessary passage of personal information if followed up. Spam can even cause a significant loss of once time. Here, in this paper we deal with those spamrsquos which may slither through filters into mail boxes of client false negative, and also those mails which are not important to a user. Here we use previous history of all those messages, opened by the client to solve the above mentioned problem. We show that for a client a particular type of messages can be unimportant mostly clientrsquos unread mails and for some other client they may be important clientrsquos read mails.Other than filtered spam generally a user decides which type of message is spam for him/her or are not important, by flagging them as a spam. Our novel approach is reducing this effort and even client need not see all those mails or flag them as spam because this filtering system and algorithms used in it will separate all those junks so that the client is left with only those mails which are useful for him/her. We propose using, part of speech tagging module of Natural Language Processing and some other discussed algorithms. This approach is not only saving time of a client but is also acting as a good mail filter. It can be considered as an addition to all those existing mail filtering techniques.