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Text clustering is one of the most researchable topics, owing to the massive usage of textual documents. The aim of text clustering algorithms is to group similar textual documents together, which can improve the data organization and makes the process of data analysis simpler. Understanding the benefits, this article intends to present a text clustering algorithm that is based on Fuzzy C Means (FCM) and Whale Optimization Algorithm (WOA). The optimization algorithm (WOA) selects the cluster centre, which helps the FCM to arrive at better textual clusters. The performance of the proposed text clustering algorithm is tested in terms of precision, recall, fmeasure, purity and entropy over three different benchmark datasets. The performance of the proposed algorithm is observed to be reasonable when compared to the existing algorithms with an average F-measure of 97.6%.