Clustering is an important technique which is used to analyze gene expression data to reveal groups of gene sharing common functional properties. With the help of the developing technology called microarray technology, clustering has now become a main technique to gene expression data analysis. Microarray technology has now made it possible to monitor the expression levels of thousands of genes during important biological processes. In this work, A Novel Hybrid Microarray Gene Expression Clustering Algorithm has been proposed which is incorporated with Hubert's Statistic Technique, Jaccard's coefficient and Dunn's Index used for cluster Validation. Its main aim is to improve the efficiency level of the quality of clusters, with optimized validation and reduce the memory requirements lower than almost all the existing clustering algorithms. It also guides in achieving high quality clusters.