Reference Material:

https://www.linkedin.com/advice/3/what-difference-between-knn-k-means-skills-computer-science-cx1hc
https://ealizadeh.com/blog/knn-and-kmeans/#:~:text=unsupervised%20learning%20algorithm.-,K%20in%20K%2DMeans%20refers%20to%20the%20number%20of%20clusters,using%20different%20values%20for%20K.
KNN does use lot of memory because in lazy learning it stores (memorizes) the training dataset. AWS sagemaker however has an improved version of this algorithm.
Because the questions does not mention we have labels, we cannot use supervised learning
K-means : unsupervised and helps us to classify different vegetables based on their many features. This also find "similar data points for each test data point"
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