VLSI Cell Partitioning plays a substantial part in VLSI physical design. The task of designing integrated circuits is multifaceted, as modern circuits have a very huge number of modules. It is very much essential to split the circuit into a smaller and meeker logic blocks. In order to build a complex digital integrated circuit, the multi million transistors must be subdivided into convenientnumber of pieces.This paper provides a heuristic approach by utilizing data mining algorithms to solve VLSI partitioning problem. A detailed study on several data mining algorithms like K-nearest neighbour, Support Vector Machine (SVM), Fuzzy c-means and K-means algorithms and their implementation in VLSI Cell Partitioning is provided.