Skin Pixel Segmentation using Variational Quantum Classifier And Quantum Support Vector Machine and Benchmarked them against traditional Learning Algorithms. Part of the SN Bose Winter Internship Program 2022, NIT silchar ** Abstract ** Quantum Computing is paving a new field for complex and parallel computation of data. With the Noisy Intermediate Scale Quantum (NISQ) technology, it is possible to simulate 4-12 qubits on real time quantum devices and with new companies entering this field, the growth is suspected to be rapid in the coming years. In this report we take a gloss over some of the aspects of quantum domain of machine learning and use it to classify viz segment skin colored pixel from other randomized pixels. The accuracy result from four types of algorithms, two classical and two quantum is presented and the conclusion drawn from my experience with the report could be summarized as ‘more amount of research and work is required for quantum machine learning algorithms to mature and outperform present day core classical Machine learning and Deep learning techniques, but that day is not nigh’.