Can I feed only images to simple CNN model without using label data?
To train the model, you need an objective to minimize. Very often, labels are used for this, for example, for an object recognition problem, to tell the model the kind of object in an image. You then train the CNN to encode features in the intermediate layers that are useful to solve this problem. The objective to minimize here has something to do with how often you identify the right object.

You can also train a model on an objective without labels, for example in an auto-encoder, where you use a CNN to find a representation of the input that has a lower dimension than the input, and then you typically use the same architecture but backwards to decode it back to the original input. The objective here is the similarity between the input and the output image.

A CNN trained this way, can be useful as a compression algorithm, because it encodes the image to some smaller representation in the middle layer of the auto-encoder, in such a way that you can rebuild the image to some level of accuracy.

So it's possible, but there is no reason to think that a CNN trained for an auto-encoder would be useful in an object recognition problem.