The coverage problem is relevant to numerous real-life applications such as agriculture, search and rescue, and demining. The primary objective of this problem is to cover as many positions as possible in an unknown environment. Utilizing multiple robots can significantly reduce the total time required for coverage while enhancing overall efficiency. In this paper, we introduce a novel Distributed Coverage Algorithm (DCA) utilizing multiple robots which is also scalable. This algorithm can be used in various real life situations like for agricultural field work, for search and rescue, etc. We formally prove termination, no overlap, correctness and time complexity of the DCA algorithm. We have simulated the DCA algorithm using the Webots multi-robot simulator and compared its performance with existing approaches. The simulation results reveal that the DCA algorithm significantly outperforms the existing approaches. DCA algorithm achieves a maximum coverage time reduction of 31.51% to 70.73% while also offering enhanced coverage efficiency in all environmental conditions.