In machine learning, one of the frequently encountered problems is grouping similar data together. You know the income level of people and now you want to group people with similar income levels together. You want to know who are the people with low income power, the people with high or very high income power, which you think can be helpful in devising a perfect marketing strategy. You have the shopping data of customers with you and now you want to group customers with similar shopping preferences together or you being the bio student want to know which cells share similar properties based upon the data about the cells you have at your hand. All the above stated problems come under the domain of an unsupervised machine learning method called clustering. Although there are a number of clustering algorithms there but when it comes to the simplest one, the award will go to K-Means clustering.