Which machine learning algorithm to choose?
If you want to use an unsupervised method i.e if your data is not labelled with classes, then something like k-means clustering may be your best bet to find patterns in the data.

Alternatively, if you want to do anomaly detection, 2 possible options are


Assuming your data is normally distributed, you could fit a Gaussian to your data and calculate the Probability Density Function (PDF). Once you have the PDF, you can set a threshold probability, below which a data point could be classified as an anomaly
If you have enough data, use a Variational Autoencoder neural network. Very roughly speaking, you train this on all the data you deem to be “normal” (the neural network learns how to reconstruct the input data in the output), and then when anomalous cases are passed to the network, it can’t reconstruct it. If the network can’t reconstruct it accurately, the data is an anomaly.