How can we use machine learning to distnguish between similarly looking images
From the images alone, assuming the links you posted are representative, I doubt a model will ever be able to predict better than random guessing.

There is a chance the model could effectively learn to read the label, but it seems like a long (and somewhat pointless) path to go down, unless you will only be predicting on labelled bottles in the future!

You will need to introduce different information with each sample, perhaps the price, amount of liquid and other such feature. At this point, you will likely want to ditch your CNN for images and instead use a standard classifier, such as Support Vector Machines or a simple feed-forward neural network.