By default, Notebook runs in a sandboxed, Google-hosted runtime. That's usually a good thing; if there's any doubt as to the integrity of the code you're running - or if you don't want to use your own machine's compute to run the program - you can just get Google's servers to do it for you. However, it also means that Colab doesn't have access to anything stored locally. Usually, this is fine since importing data into Colab (whether by mounting your drive or uploading individual files) will serve the purpose you need.
If you're still very certain that you want to run locally - which gives Colab access to your local files but also loses all the benefits of a sandbox - you can start a "local runtime". For the VS Code extension, you do this by clicking "Select Kernel" in the top right and choosing "Python Environments" rather than "Colab".
If you're on the web, the local runtime documentation says you'll need to run the following Jupyter Notebook command (given that you've already installed Jupyter):
jupyter notebook \
--NotebookApp.allow_origin='https://colab.research.google.com' \
--port=8888 \
--NotebookApp.port_retries=0 \
--NotebookApp.allow_credentials=True
Then, click the "Connect" button (where you would usually select your parameters for running the program, such as CPU/GPU type) and choose "Connect to local runtime...", entering arguments from the above command's output as they are requested.
uploadthem on Google Drive or on space in Google Colab (virtual) machine. (files.upload()). I don't remeber but there is method to run Google Colab with access to local files (and then it doesn't have access to Google Drive) but it may need some settings.Google Colabuses to access local files and execute code. So all this needs a lot of work and it can be useless if you need access to GPU/TPU.