<｜begin▁of▁sentence｜>### Instruction:
As a rehabilitation counselor assisting an individual with visual impairments, imagine that a graph represents the layout of a familiar environment, such as a university campus. The edges of the graph correspond to walkways and paths between buildings. After calculating the minimum Vertex Cover, you need to assist in extracting and printing the edges of the subgraph corresponding to the first cluster in the Vertex Cover. This will help the individual understand the most essential paths within the campus for accessibility and navigation. You can utilize the NetworkX library in Python to manage and analyze the graph data.
### Response:
from igraph import Graph

# Define the edges for the graph
edges = [(0, 1), (1, 2), (2, 3), (3, 4), (4, 0), (1, 3)]

# Create a graph and calculate the minimum Vertex Cover
graph = Graph(edges=edges, directed=False)
vertex_cover = graph.mincut().partition

# Get the subgraph for the first cluster in the Vertex Cover
cluster_index = 0
subgraph = vertex_cover.subgraph(idx=cluster_index)

# Print the edges of the subgraph
print('Subgraph edges:', subgraph.get_edgelist())
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