No any instances will be directly associated with 'Car' and Product, and any potential intermediate nodes in the hierarchy. How does this solution compare with the solution of directly putting Product, Car and Electric_Car as 3 labels on 'Tesla Model S', without creating the hierarchy. What are pros and cons of these 2 approaches?
The pros and cons of these two approaches are dependent on your use case and what you're trying to do with this data, and no one else can answer this for you. More analysis on what you're trying to accomplish is needed to make this answerable.
From a search perspective, it seems multiple labels will be more efficient, while the Is_A relationship needs inference to answer questions like "Is Tesla Model S a car?"
I wouldn't worry about efficiency first. Worry about simplicity of query, and fidelity to your overall data model first. Worry about query efficiency only later when you have a specific query in mind. But for the record, if you index the "name" attribute, and you look up a node by both its label and name, that's going to be a very efficient lookup, and adding extra labels isn't really going to help you much.
The benefit of the hierarchy approach is that it can organize all cars under the "Car" node, creating a more connected graph visually.
Maybe. But this goes to the details of your use case. How connected the graph is visually implies that what you want to do with this graph is visualize it primarily, and that may not be the case.
The better way to go about this is to start with your "money queries". Why are you building this system in the first place? Usually, it boils down to 5-7 at most "money queries", the things that you want your database to be able to answer that drive most of the value. While visualizing the graph is quite nice, usually that's not the primary purpose. Focus on those money queries first will crystalize a lot about how best to do the data model and arrange things for easy query. Not knowing what questions you want to ask of the graph, it's near impossible for anyone to give good modeling advice, because data models exist to facilitate answers to queries.