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An extraordinary outbreak of pneumonia in Wuhan City, China, was subsequently termed as COVID-19 emerged in December 2019. The virus is also known as an infectious disease inherited from a novel coronavirus. This study exposed the beginning of the unprecedented COVID-19 confirmed cases spike exponentially in the United States and 200 countries globally. Epidemiologists usually utilize conventional spread prediction via the classic clustering method. A suspected patient is likely to blow out the disease to a potential agglomerative of cases grouped in place and time. In the era of cutting edge, outbreak prediction can also generate accurate techniques to utilize unsupervised machine learning methods. We apply two prominent unsupervised learning methods, namely K-means clustering and correlation on a set Coronavirus Outbreak COVID-19 data collection dated March 27 and August 16, 2020. The K …